CN118810829A - A Steering-Differential Yaw Stability Control Method for Actuator Failure - Google Patents

Abstract

The present invention discloses a steering-differential yaw stability control method for actuator failure, the method of the present invention includes calculating constraint auxiliary variables based on vehicle dynamics state information, fault information and environmental information and according to the difference matrix between the target execution command calculated at the last moment and the actual execution command; observing and fitting the yaw stability control disturbance matrix based on a radial basis function neural network to obtain the disturbance matrix observation value of the yaw stability control; calculating the intermediate control variable target value based on the constraint auxiliary variable and the disturbance matrix observation value; allocating the intermediate control variable target value based on the actuator execution capability, calculating the control command executed by the actuator; and executing the corresponding control command through the actuator. In the actuator failure scenario, the present invention makes full use of the remaining execution capability, reduces the yaw tracking performance degradation caused by the decline in execution capability, and makes the differential steering participation in the yaw control process safer and more stable.

Description

A Steering-Differential Yaw Stability Control Method for Actuator Failure

Technical Field

The invention relates to the technical field of intelligent automobile control, and in particular to a steering-differential yaw stability control method facing actuator failure.

Background Art

With the development of intelligent automotive technology, high-level autonomous driving functions have increasingly higher requirements for vehicle execution and vehicle safety. The integration and coordinated control of the vehicle chassis steering, drive and braking systems are key technologies to improve vehicle safety and driving performance. The coordination of different systems also provides a cross-system execution solution for the vehicle after a single execution system fails, such as relying on the redundant backup of the steering system by the drive/brake system.

Traditional vehicle yaw stability control relies on the normal operation of the actuators and adopts a hierarchical control architecture, where actuator commands are directly distributed after yaw control. However, when one or more key actuators fail, the execution capability of the execution subsystem is limited, and it may be difficult to implement the original yaw control command. In the case of partial or complete failure of the actuator, the existing technology fails to provide an effective solution to maintain the yaw stability of the vehicle, especially in emergency maneuvers or extreme driving conditions.

With the advancement of autonomous driving and domain control technologies, vehicles have more precise control over themselves and higher safety requirements under fault conditions. Failure operation control of vehicles after a fault becomes particularly important. Therefore, it is particularly important to develop a control method that can maintain the vehicle's yaw stability when the steering, drive or brake actuators of smart cars fail and the execution capability of the execution subsystem is degraded.

Summary of the invention

The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

To this end, the present invention proposes a steering-differential yaw stability control system for actuator failure. Aiming at the deviation between the execution command output by the yaw controller and the actual execution, the output of the yaw controller is adjusted by designing constrained auxiliary variables, thereby reducing the deviation between the yaw controller and the lower-level execution command allocation, thereby meeting various performance indicators and safety requirements of the steering-differential yaw stability control in fault scenarios.

Another object of the present invention is to provide a steering-differential yaw stability control method for actuator failure.

To achieve the above-mentioned object, the present invention proposes a steering-differential yaw stability control system for actuator failure, comprising a sensor combination module, a dynamic fusion observation module, a yaw tracking control module and an actuator subsystem; wherein,

The sensor combination module is used to output vehicle-related sensor information;

The dynamics fusion observation module is used to receive the vehicle-related sensor information and output vehicle dynamics state feedback information and vehicle actuator fault state feedback information;

The yaw tracking control module is used to receive the yaw tracking angular velocity control command input by the self-driving system or the vehicle driver, and calculate the actuator's remaining execution capacity based on the received vehicle actuator fault state feedback information, and perform yaw tracking stability control feedback control based on the received vehicle dynamics state feedback information, and output a control command for the actuator subsystem.

The steering-differential yaw stability control system for actuator failure according to the embodiment of the present invention may also have the following additional technical features:

In one embodiment of the present invention, the yaw tracking control module comprises:

An execution constraint auxiliary unit, used for calculating a constraint auxiliary variable according to a difference between a target execution command and an actual execution command, so as to assist yaw stability control;

A disturbance observation unit, used to calculate the observation value of the yaw stability control disturbance matrix;

A yaw stability control unit, for calculating a control variable target value of yaw stability control based on the observation value of the constraint auxiliary variable and the disturbance matrix and according to the yaw control target and the vehicle dynamics state feedback information;

The execution command distribution unit is used to distribute the actuator to the control variable target value generated by the yaw stability control unit to generate the front wheel steering angle, braking system and driving system control commands.

In one embodiment of the present invention, the execution constraint auxiliary unit is used to receive the difference between the target execution command calculated by the execution command allocation unit at the previous moment and the actual execution command, and construct a calculation constraint auxiliary variable based on the difference, and send the constraint auxiliary variable to the yaw stability control unit;

The disturbance observation unit is used to perform disturbance observation by inputting the difference between the yaw control target of the system and the feedback state of the vehicle dynamics state, observe and fit the yaw stability control disturbance using a radial basis function neural network, and send the fitted disturbance matrix observation value to the yaw stability control unit for feedforward control;

The yaw stability control unit is used to receive the constraint auxiliary variable and the disturbance matrix observation value, and perform feedback control according to the yaw control target of the input system and the dynamic state feedback state difference, and calculate the intermediate control variable of the yaw stability control; when the constraint auxiliary variable is not zero, adjust the intermediate control variable output according to the constraint auxiliary variable, and output it to the execution command allocation unit;

The execution command allocation unit is used to receive the input of the intermediate control variable, and to allocate the actuator command in combination with the remaining execution capacity of the actuator and the driving demand of the whole vehicle, so as to generate the execution command of the actuator subsystem and calculate the execution allocation error.

In one embodiment of the present invention, the sensor combination module includes multiple types of laser radar, camera combination, GPS, and IMU; the actuator subsystem includes: a wire-controlled brake system for four-wheel independent braking, a wire-controlled drive system for four-wheel independent driving, and a wire-controlled steering system; the dynamics fusion observation module includes a fault identification unit and a dynamics state identification unit; wherein,

The dynamic fusion observation module receives the vehicle-related sensor information output by the sensor combination module and the actuator sensor feedback information fed back by the actuator subsystem; the vehicle-related sensor information and the actuator sensor feedback information are fused and calculated by the fault identification unit and the dynamic state identification unit respectively to obtain the corresponding vehicle actuator fault state feedback information and vehicle dynamic state feedback information, and transmit them to the yaw tracking control module.

To achieve the above object, the present invention provides, on the other hand, a steering-differential yaw stability control method for actuator failure, comprising:

Obtain vehicle dynamics status information, fault information and environmental information;

Calculating constraint auxiliary variables based on the vehicle dynamics state information, fault information and environmental information and according to a difference matrix between a target execution command calculated at a previous moment and an actual execution command;

Based on the radial basis function neural network, the disturbance matrix of yaw stability control is fitted to obtain the observation value of the disturbance matrix of yaw stability control;

Calculate the target value of the intermediate control variable based on the constraint auxiliary variables and the disturbance matrix observation value;

Assigning target values of intermediate control variables based on the execution capabilities of the actuators and calculating control commands executed by the actuators;

The corresponding control command is executed by the actuator, wherein the positive value of the four-wheel drive/braking torque is executed by the wheel drive system of the corresponding actuator, the negative value is coordinated and controlled by the corresponding wheel braking and drive system of the actuator, and the front wheel steering angle command is executed by the steering system of the actuator.

The steering-differential yaw stability control system and method for actuator failure in the embodiments of the present invention need to be able to dynamically adjust the yaw control command output and optimize the distribution of yaw torque according to the actual operating status of the remaining actuators, so as to ensure the safety and stability of the vehicle even when some actuators fail, thereby meeting the various performance indicators and safety requirements of the steering-differential yaw stability control in fault scenarios.

Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

1 is a structural diagram of a steering-differential yaw stability control system for actuator failure according to an embodiment of the present invention;

FIG. 2 is a flow chart of a steering-differential yaw stability control method for actuator failure according to an embodiment of the present invention.

DETAILED DESCRIPTION

It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

The following describes a steering-differential yaw stability control system and method for actuator failure according to an embodiment of the present invention with reference to the accompanying drawings.

FIG1 is a structural diagram of a steering-differential yaw stability control system for actuator failure according to an embodiment of the present invention. As shown in FIG1 , a sensor combination module 100, a dynamics fusion observation module 200, a yaw tracking control module 300 and an actuator subsystem 400 are provided; wherein,

The sensor combination module 100 is used to output vehicle-related sensor information;

A dynamics fusion observation module 200, used to receive the vehicle-related sensor information and output vehicle dynamics state feedback information and vehicle actuator fault state feedback information;

The yaw tracking control module 300 is used to receive the yaw tracking angular velocity control command input by the self-driving system or the vehicle driver, and calculate the actuator's remaining execution capacity based on the received vehicle actuator fault state feedback information, and perform yaw tracking stability control feedback control based on the received vehicle dynamics state feedback information, and output a control command for the actuator subsystem 400.

It can be understood that the purpose of the present invention is to perform differential-steering yaw stability control in actuator failure scenarios for high-level autonomous driving vehicles by combining fault information, environmental information, and vehicle status information, so as to make full use of the actuator's remaining execution capacity as much as possible while meeting the vehicle's stable operation requirements.

In one embodiment of the present invention, the yaw tracking control module 300 includes: an execution constraint auxiliary unit, which calculates the difference between the target execution command and the actual execution command, calculates the constraint auxiliary variable, and assists the yaw stability control; a disturbance observation unit, which calculates the observation value of the yaw stability control disturbance matrix; a yaw stability control unit, which combines the constraint auxiliary variable and the disturbance matrix observation value and calculates the control variable target value of the yaw stability control based on the yaw control target and the dynamic state feedback information; an execution command allocation unit, which performs actuator allocation on the target execution command generated by the yaw stability control unit, and generates the front wheel steering angle, braking system and drive system control commands.

Preferably, the execution constraint auxiliary unit receives the difference between the target execution command and the actual execution command calculated by the allocation module at the previous moment, and constructs a calculation constraint auxiliary variable based on the execution command difference, and transmits it to the yaw stability control unit.

Preferably, the disturbance observation unit performs disturbance observation by inputting the system's yaw control target and the dynamic state feedback state difference, and can use a radial basis function neural network to observe and fit the yaw stability control disturbance, and transmit it to the yaw stability control unit for feedforward control.

Preferably, the yaw stability control unit receives the constraint auxiliary variable and the disturbance matrix observation value, performs feedback control according to the yaw control target of the input system and the dynamic state feedback state difference, and calculates the intermediate control variable of the yaw stability control. When the constraint auxiliary variable is not zero, the intermediate control variable output needs to be adjusted according to the constraint auxiliary variable and transmitted to the execution command allocation unit.

Preferably, the execution command allocation unit receives the input of the intermediate control variable, and allocates the actuator command in combination with the remaining execution capacity, the vehicle drive demand, etc. At the same time, in order to reduce the deterioration of the yaw tracking performance caused by insufficient execution capacity, the allocation process constrains the deterioration of the yaw stability control performance (control of the derivative of the Lyapunov function) caused by the execution allocation error, and minimizes the impact on the overall control effect. Finally, the execution command of the actuator control subsystem is generated and transmitted to the actuator subsystem, and the execution allocation error is calculated.

In one embodiment of the present invention, the dynamic fusion observation module 200 receives the sensor information transmitted by the sensor combination and the actuator sensor feedback information fed back by the actuator subsystem, and the fault identification unit and the dynamic state identification unit respectively perform fusion calculations to obtain the vehicle actuator fault state feedback information and the vehicle dynamic state feedback information, and transmit them to the yaw tracking control module.

In one embodiment of the present invention, the sensor combination module 100 includes a laser radar, a camera combination, a GPS, an IMU, etc., and transmits the measured vehicle-related sensor information to the dynamics fusion observation module 200.

In one embodiment of the present invention, the actuator subsystem 400 includes: a wire-controlled brake system for four-wheel independent braking, a wire-controlled drive system for four-wheel independent driving, and a wire-controlled steering system. The actuator subsystem executes the actuator subsystem execution command generated by the yaw tracking module.

According to the steering-differential yaw stability control system for actuator failure according to the embodiment of the present invention, an execution constraint auxiliary unit is introduced into the yaw stability control process of the vehicle, so that the yaw stability control at the dynamic level and the execution command allocation task at the underlying execution level are feedback coordinated. When the yaw stability control output exceeds the existing remaining execution capacity, the output can be adjusted quickly and adaptively, thereby reducing the risk of system instability caused by the mismatch between the execution command allocation and the yaw stability control output.

In order to implement the above embodiment, as shown in FIG2 , this embodiment further provides a steering-differential yaw stability control method for actuator failure, including:

S1, obtain vehicle dynamics status information, fault information and environmental information.

It can be understood that the present invention obtains the vehicle dynamics state, fault information and environmental information for fusion calculation.

The present invention obtains the current vehicle speed v _x , yaw rate γ, sideslip angle β and current road adhesion coefficient μ through a fusion algorithm, and simultaneously obtains the remaining execution capacity of the actuator under the fault condition according to the fault information identification, and calculates the fault matrix:

Among them, Λ is the fault information matrix, They are the remaining actuator capacity coefficients of the steering system and the four wheel drive/brake systems, representing the ratio of the remaining execution capacity to the execution capacity in the absence of faults; is a function that generates a matrix based on diagonal elements.

Modeling vehicle dynamics considering differential and steering coordinated yaw stability control:

where x = [βγ] ^T is the yaw stability control state variable vector; A is the yaw stability control state transfer matrix; _Bv is the yaw stability control input matrix; τ is the intermediate control variable of the yaw stability control model, and τ = _Buu ; u = [ _δf T _fl T _fr T _rl T _rr ] ^T is the control input vector of yaw stability control, _δf is the front wheel steering angle, _Tij is the four-wheel drive/braking torque command (ij = fl, fr, rl, rr, representing the left front, right front, left rear, and right rear wheels, respectively); d is the yaw stability control disturbance matrix; _lf and _lr are the distances from the front axle to the center of mass and the distance from the rear axle to the center of mass, respectively; R is the effective rolling radius of the vehicle tire; w is the vehicle wheelbase; _Cf and _Cr are the tire cornering stiffness of the front and rear axles of the vehicle, respectively; _Iz is the z-axis moment of inertia of the vehicle, and m is the vehicle mass.

S2, based on the vehicle dynamics state information, fault information and environmental information and according to the difference matrix between the target execution command calculated at the last moment and the actual execution command, calculate the constraint auxiliary variables.

Specifically, based on the vehicle dynamics state information, fault information and environmental information, and by receiving the target execution command and the actual execution command difference matrix calculated by the execution command allocation unit of the yaw tracking control module at the previous moment Compute the constrained auxiliary variable α.

Difference matrix between target execution command and actual execution command It can be calculated as:

Among them, τ is the target execution command, and l(τ) is the actual execution command.

The differential equation for implementing the constraint on the auxiliary variable α is:

in, To execute the constraint, the auxiliary variable α is the derivative; _P1 and _P2 are the positive definite matrices defined by the control objective, which need to be set by yourself; _Ka is the control parameter, which needs to be set by yourself.

By implementing the constraint auxiliary quantity derivative The execution constraint auxiliary variable α at the corresponding moment can be obtained by integration.

S3, performing observation fitting on the yaw stability control disturbance matrix based on the radial basis function neural network to obtain the disturbance matrix observation value of the yaw stability control.

Specifically, the yaw stability control disturbance matrix d is observed and fitted based on the radial basis function (RBF) neural network to obtain the observed value of the yaw stability control disturbance matrix: Observations of the perturbation matrix It can be calculated by the following RBF neural network:

in, is the weight matrix of the RBF neural network, which is updated in real time according to the error during the observation and estimation process; is the radial basis function of the RBF neural network, which can be selected as a Gaussian function.

The weighted matrix update rate of the RBF neural network is designed to be:

in, is the derivative matrix of the weighted matrix of the RBF neural network; Γ is the gain matrix, which needs to be designed by yourself; the weighted error η＝(P ₁ +P ₂ ) ^T e+P ₂ a, and e＝xx _d is the state error of the yaw angular velocity tracking process; r is the gain parameter, which needs to be designed by yourself.

According to the derivative of the weighting matrix calculated Weighted Matrix By performing integral updating, an accurate estimation of the pendulum stabilization control disturbance matrix can be achieved.

S4, calculates the target value of the intermediate control variable based on the constrained auxiliary variables and the disturbance matrix observations.

Specifically, based on the execution constraint auxiliary variable α and the disturbance matrix observation value calculated in the above steps The intermediate control variable target value τ can be calculated according to the following formula:

Where x _d = [β _d γ _d ] ^T is the target state of yaw stability control, is the derivative of _xd ; _K1 and _K2 are control gains, which need to be designed by yourself.

S5, allocating the target value of the intermediate control variable based on the execution capability of the actuator, and calculating the control command executed by the actuator.

Specifically, the intermediate control variable target value τ is allocated based on the actuator execution capability, the actuator execution command is calculated, and the intermediate control variable execution deviation is calculated. The intermediate control variable target value τ calculated in step S4 can be decomposed by solving the following optimization problem:

Cu-δ ₂ =T _acc ,

Λu _min ≤u≤Λu _max .

In the formula, for The optimized solution value of , δ ₁ is the first slack variable, δ ₂ is the second slack variable; W _u , W _τ are the definition matrices of the optimization objective, are the definition parameters of the optimization objective function, all of which are optimization design parameters; C is the drive coefficient matrix, C=[01111]; u _min and u _max are the maximum value vector and minimum value vector of the control input respectively; T _acc is the target vehicle drive torque required to maintain the vehicle speed.

At the same time, the actual execution command l(τ) = Bu _u can calculate the execution deviation of the intermediate control variable

For the above optimization problem, by introducing the slack variable δ ₁ and designing the corresponding optimization constraints, the influence of the allocation process on the control of the Lyapunov function V(e) = e ^T Pe can be reduced, and the deterioration of the control performance caused by insufficient execution capability can be minimized within the remaining execution capability of the vehicle, thereby ensuring the yaw stability control accuracy and meeting the vehicle speed maintenance requirements.

S6, execute the corresponding control command through the actuator, wherein the positive value of the four-wheel drive/braking torque is executed by the wheel drive system of the corresponding actuator, the negative value is coordinated and controlled by the corresponding wheel braking and drive system of the actuator, and the front wheel steering angle command is executed by the steering system of the actuator.

Specifically, the actuator executes the corresponding control command, the positive value of the four-wheel drive/braking torque _Tij is executed by the corresponding wheel drive system, the negative value is coordinated and controlled by the corresponding wheel braking and drive system, and the front wheel steering angle command _δf is executed by the steering system.

In summary, through the interaction between the yaw controller and the lower-level execution command allocation, when the actuator fails and the execution capability decreases, the deterioration of the yaw stability control performance caused by insufficient execution capability is minimized at the allocation layer, and the execution deviation of the intermediate control variable is fed back to the yaw controller. The output of the yaw controller is adjusted by designing constrained auxiliary variables to reduce the deviation between the yaw controller and the lower-level execution command allocation, thereby making full use of the remaining execution capability, making the differential steering participation in the yaw control process safer and more stable, and meeting the various performance indicators and safety requirements of steering-differential yaw stability control under fault scenarios. At the same time, this technology also supports the development of autonomous driving technology, ensuring that the vehicle can still maintain basic control safety when the key system fails partially or completely, and promotes the widespread application of autonomous driving vehicles.

The steering-differential yaw stability control method for actuator failure according to the embodiment of the present invention can significantly improve the safety and stability of the vehicle when the actuator fails. In view of the deviation between the output execution command of the yaw controller and the actual execution, the output of the yaw controller is adjusted by designing a constrained auxiliary variable to reduce the deviation between the yaw controller and the lower-level execution command allocation, thereby meeting multiple performance indicators and safety requirements of the steering-differential yaw stability control in the fault scenario.

In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

Claims (10)

1. A steering-differential yaw stability control system for an actuator failure, comprising: the system comprises a sensor assembly module, a dynamics fusion observation module, a yaw tracking control module and an execution mechanism subsystem; wherein,

The sensor module is used for outputting vehicle-related sensing information;

the dynamics fusion observation module is used for receiving the vehicle-related sensing information and outputting vehicle dynamics state feedback information and vehicle actuator fault state feedback information;

The yaw tracking control module is used for receiving a yaw tracking angular velocity control command input by a self-driving system or a vehicle driver, calculating the residual execution capacity of an actuator according to the received fault state feedback information of the actuator of the vehicle, simultaneously carrying out yaw tracking stability control feedback control according to the received dynamic state feedback information of the vehicle, and outputting a control command for an actuator subsystem.

2. The system of claim 1, wherein the yaw tracking control module comprises:

an execution constraint assisting unit for calculating a constraint assisting variable to assist yaw stability control based on a difference between the target execution command and the actual execution command;

The disturbance observation unit is used for calculating an observation value of the yaw stability control disturbance matrix;

A yaw stability control unit for calculating a control variable target value of yaw stability control based on the observed values of the constraint auxiliary variable and the disturbance matrix and according to the yaw control target and the vehicle dynamics state feedback information;

And the execution command distribution unit is used for performing actuator distribution on the control variable target value generated by the yaw stability control unit so as to generate front wheel steering angle, a braking system and a driving system control command.

3. The system of claim 2, wherein the system further comprises a controller configured to control the controller,

The execution constraint auxiliary unit is used for receiving the difference value between the target execution command and the actual execution command calculated by the execution command distribution unit at the previous moment, constructing a calculation constraint auxiliary variable based on the difference value, and sending the constraint auxiliary variable to the yaw stability control unit;

The disturbance observation unit is used for carrying out disturbance observation through a yaw control target of the input system and a vehicle dynamics state feedback state difference value, carrying out observation fitting on yaw stability control disturbance by adopting a radial basis function neural network, and sending a fitted disturbance matrix observation value to the yaw stability control unit for feedforward control;

the yaw stability control unit is used for receiving the constraint auxiliary variable and the disturbance matrix observation value, performing feedback control according to a yaw control target of the input system and a dynamic state feedback state difference value, and calculating an intermediate control variable of yaw stability control; when the constraint auxiliary variable is not zero, adjusting the output of the intermediate control variable according to the constraint auxiliary variable and outputting the output to the execution command distribution unit;

the execution command distribution unit is used for receiving the input of the intermediate control variable, and carrying out the distribution of the executor command by combining the residual execution capacity of the executor and the whole vehicle driving requirement so as to generate an execution command of the execution mechanism subsystem and calculate an execution distribution error.

4. The system of claim 3, wherein the sensor assembly comprises a plurality of lidar, camera assemblies, GPS, IMU; the actuator subsystem includes: a four-wheel independent braking wire control system, a four-wheel independent driving wire control driving system and a wire control steering system; the dynamics fusion observation module comprises a fault identification unit and a dynamics state identification unit; wherein,

The dynamics fusion observation module receives vehicle-related sensing information output by the sensor assembly module and actuator sensing feedback information fed back by the actuator subsystem; and respectively carrying out fusion calculation on the vehicle-related sensing information and the actuating mechanism sensing feedback information through a fault recognition unit and a dynamics state recognition unit to obtain corresponding vehicle actuator fault state feedback information and vehicle dynamics state feedback information, and transmitting the corresponding vehicle actuator fault state feedback information and the corresponding vehicle dynamics state feedback information to a yaw tracking control module.

5. A steering-differential yaw stability control method for actuator failure is characterized in that,

Acquiring vehicle dynamics state information, fault information and environment information;

Calculating constraint auxiliary variables based on the vehicle dynamics state information, fault information and environment information and according to a difference matrix of the target execution command and the actual execution command calculated at the previous moment;

performing observation fitting on the yaw stability control disturbance matrix based on the radial basis function neural network to obtain a disturbance matrix observation value of yaw stability control;

Calculating an intermediate control variable target value based on the constraint auxiliary variable and the disturbance matrix observation value;

Distributing the intermediate control variable target value based on the execution capacity of the executor, and calculating a control command executed by the executor;

The corresponding control command is executed by the actuator, wherein a positive value in the four-wheel drive/braking torque is executed by the wheel drive system of the corresponding actuator, the corresponding wheel braking and drive system of the actuator is coordinated and controlled, and the front wheel steering angle command is executed by the steering system of the actuator.

6. The method of claim 5, wherein after acquiring the vehicle dynamics state information, the malfunction information, and the environment information, the method further comprises:

The vehicle dynamics state information, the fault information and the environment information are fused through a fusion algorithm to obtain a current vehicle speed v _x, a yaw rate gamma, a slip angle beta and a current road attachment coefficient mu, and the residual execution capacity of the actuator under the fault condition is obtained through recognition based on the fault information to calculate a fault matrix;

Wherein, lambda is the fault information matrix, The residual actuator capacity coefficients of the steering system and the four wheel driving/braking systems represent the residual actuator capacity and the actuator capacity ratio value under the fault-free condition; generating a function of the matrix for the diagonal elements;

Modeling based on vehicle dynamics of differential and steering cooperative yaw stability control:

Wherein x= [ βγ ] ^T is a yaw stability control state variable vector; a is a yaw stability control state transition matrix; b _v is a yaw stability control input matrix; τ is an intermediate control variable of the yaw stability control model, τ=b _uu;u＝[δ_f T_fl T_frT_rl T_rr]^T is a control input vector of the yaw stability control, δ _f is a front wheel steering angle, and T _ij is a four wheel drive/braking force torque command; ij=fl, fr, rl, rr, respectively representing front left, front right, rear left, rear right wheels; d is a yaw stability control disturbance matrix; l _f and l _r are the front axle to centroid distance and rear axle to centroid distance, respectively, of the vehicle; r is the effective rolling radius of the vehicle tyre; w is the track of the vehicle; c _f and C _r are the tire cornering stiffness of the front and rear axles of the vehicle, respectively; i _z is the z-axis moment of inertia of the vehicle, and m is the mass of the whole vehicle.

7. The method according to claim 6, wherein the difference matrix between the target execution command and the actual execution command calculated at the previous time is calculatedCalculating a constraint auxiliary variable α, comprising:

Difference matrix of target execution command and actual execution command

Wherein τ is a target execution command, and l (τ) is an actual execution command;

The differential equation for the execution constraint auxiliary variable α is:

wherein, To perform constraint on the auxiliary variable alpha derivative; p ₁ and P ₂ are positive definite matrixes defined by control targets, and K _a is a control parameter.

8. The method of claim 7, wherein the yaw stability control disturbance matrix d is fitted by observation based on a radial basis function neural network to obtain a disturbance matrix observation of yaw stability controlComprising the following steps:

wherein, A weighting matrix for the RBF neural network; radial basis functions of the RBF neural network;

The update rate of the weighting matrix of the RBF neural network is as follows:

wherein, A derivative matrix that is a weighting matrix of the RBF neural network; Γ is the gain matrix; the weighting error η= (P ₁+P₂)^Te+P₂ a, and e=x-x _d is the state error of the yaw-rate tracking process, r is the gain parameter.

9. The method of claim 8, wherein the constraint-based auxiliary variable α and the perturbation matrix observations are based onCalculating an intermediate control variable target value τ, comprising:

Wherein x _d＝[β_dγ_d]^T is the yaw stability control target state, Is x _d derivative; k ₁、K₂ is the control gain.

10. The method according to claim 9, characterized in that the intermediate control variable target value τ is decomposed by solving the following optimization problem:

Cu-δ₂＝T_acc,

Λu_min≤u≤Λu_max.

wherein, Is thatDelta ₁ is a first relaxation variable and delta ₂ is a second relaxation variable; w _u、W_τ is a defined matrix of optimization objectives,The definition parameters for optimizing the objective function are all optimization design parameters; c is a driving coefficient matrix, C= [01111];

u _min、u_max is the maximum value vector and minimum value vector of the control input respectively; t _acc is the target whole vehicle driving torque required for maintaining the vehicle speed;

Actual execution command l (τ) =b _u u, calculate intermediate control variable execution bias